U.S. patent number 7,656,932 [Application Number 11/429,452] was granted by the patent office on 2010-02-02 for digital receiver device.
This patent grant is currently assigned to STMicroelectronics (Rousset) SAS, Universite de Provence (AIX Marseille I). Invention is credited to Anne Collard Bovy, Philippe Courmontagne, Beno t Durand, Christophe Fraschini, Stephane Meillere.
United States Patent |
7,656,932 |
Durand , et al. |
February 2, 2010 |
Digital receiver device
Abstract
A digital processing device for a modulated signal, arranged at
the input of a radio frequency receiver chain, suited in particular
to a transmission system a direct sequence spread spectrum
operation, comprising an analog-to-digital converter performing
undersampling of the signal received, leading to an overlapping of
the frequency range of the undersampled wanted signal by the
frequency range of an interfering signal, demodulation means
connected at the output of the analog-to-digital converter in order
to bring the undersampled wanted signal back to baseband, a low
pass filter connected at the output of the demodulation means and a
filter matched to the spreading code used, and an additional
filtering unit arranged between the low pass filter and the matched
filter, for implementing a stochastic matched filtering operation
to improve the signal-to-noise ratio at the input of the matched
filter.
Inventors: |
Durand; Beno t (Rousset,
FR), Fraschini; Christophe (La Garde, FR),
Courmontagne; Philippe (Belgentier, FR), Collard
Bovy; Anne (Bouc Bel Air, FR), Meillere; Stephane
(Nedules, FR) |
Assignee: |
STMicroelectronics (Rousset)
SAS (Rousset, FR)
Universite de Provence (AIX Marseille I) (Marseille Cedex,
FR)
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Family
ID: |
37419074 |
Appl.
No.: |
11/429,452 |
Filed: |
May 4, 2006 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20060262833 A1 |
Nov 23, 2006 |
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Foreign Application Priority Data
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May 4, 2005 [FR] |
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05 04588 |
May 4, 2005 [FR] |
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05 04589 |
May 4, 2005 [FR] |
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05 04591 |
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Current U.S.
Class: |
375/143; 375/343;
375/144 |
Current CPC
Class: |
H04B
1/30 (20130101); H04B 1/7093 (20130101) |
Current International
Class: |
H04B
1/00 (20060101) |
Field of
Search: |
;375/147,136,316,324,340,143-144 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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1 339 167 |
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Aug 2003 |
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EP |
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2 573 589 |
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May 1986 |
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FR |
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Other References
JF. Cavassilas, B. Xerri; "Extension de la notion de filtre adapte.
Contribution a la detection de signaux courts en presence de termes
perturbateurs", Revue Traitement Du Signal, vol. 10, No. 3, 1992,
pp. 215-221, XP002363859. cited by other .
Canales T J et al; "Adaptive Stochastic Filters", Proceedings of
the Midwest Symposium on Circuits and Systems, Champaign, Aug.
14-16, 1989, New York, IEEE, US, vol. vol. 1 Symp. 32, Aug. 14,
1989, pp. 609-612, XP000139728. cited by other .
Lakkis I et al; "Optimum eigenfilters and matched filters",
Electronics Letters, IEE Stevenage, GB, vol. 32, No. 22, Oct. 24,
1996, pp. 2068-2070, XP006005913. cited by other .
Rasmussen J L et al; "An adaptive technique for designing minimum
phase models", Signals, Systems and Computers, 1991. 1991
Conference Record of the Twenty-Fifth Asilomar Conference on
Pacific Grove, CA, USA Nov. 4-6, 1991, Los Alamitos, CA, USA, IEEE
Comput. Soc, US, Nov. 4, 1991, pp. 654-658, XP010026383. cited by
other .
Stewart K A; "Effect of sample clock jitter on IF-sampling Is-95
receivers", Personal, Indoor and Mobile Radio Communications, 1997.
Waves of the Year 2000, PIMRC '97., The 8.sup.th IEEE International
Symposium on Helsinki, Finland Sep. 1-4, 1997, New York, NY, USA,
IEEE, US, vol. 2, Sep. 1, 1997, pp. 366-370, XP010247670. cited by
other .
Jean-Francois Cavassilas; "Le filtrage adapte stochastique",
Internet Article, Online! XP002363860 Extrait de l'Internet:
URL:http://cava.unit-tln.fr/Adapte.pdf> 'extrait le Jan. 20,
2006! cited by other .
French Search Report for FR 0504591 dated Feb. 6, 2006. cited by
other .
French Search Report for FR 0504589 dated Feb. 6, 2006. cited by
other .
French Search Report for FR 0504588 dated Feb. 6, 2006. cited by
other.
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Primary Examiner: Bayard; Emmanuel
Attorney, Agent or Firm: Jablonski; Kevin D. Graybeal
Jackson LLP
Claims
The invention claimed is:
1. Digital processing device for a modulated signal, arranged at
the input of a radio frequency receiver chain, suited in particular
to a transmission system using binary carrier phase modulation by
means of a binary message on which a direct sequence spread
spectrum operation has been carried out, this device comprising an
analog-to-digital converter performing undersampling of the signal
received, leading to an at least partial overlapping of the
frequency range of the undersampled wanted signal by the frequency
range of an interfering signal, demodulation means connected at the
output of the analog-to-digital converter in order to bring the
undersampled wanted signal back to baseband, a low pass filter
connected at the output of the demodulation means and a filter
matched to a spreading code used, wherein said device includes an
additional filtering unit arranged between the low pass filter and
the matched filter, said filtering unit implementing a stochastic
matched filtering operation to improve the signal-to-noise ratio at
the input of the filter matched to the spreading code.
2. Processing device as claimed in claim 1 wherein the additional
filtering unit includes a plurality Q of finite response base
filters mounted in parallel, each of which receives the
undersampled signal supplied at the output of the low pass filter,
each filter being characterized by a set of N coefficients, this
number N being determined such that it corresponds to the minimum
number of samples for describing one bit of the spread message, the
coefficients of each of the Q filters corresponding respectively to
components of Q eigen vectors associated with at least Q eigen
values greater than 1 of a matrix B.sup.-1A, where B is the
variance-covariance matrix of the interfering signal and A the
variance-covariance matrix of the wanted signal.
3. Processing device as claimed in claim 2 wherein for each filter
of the plurality Q of finite response filters, the additional
filtering unit includes means for multiplying the signal obtained
at the output of said filter, with, respectively, the central
coefficient of the vector resulting from the product between the
variance-covariance matrix of the interfering signal and the eigen
vector defining the coefficients of said filter, said unit further
comprising means of summing up the vectors resulting from all of
these operations, supplying a signal corresponding to the output
signal of the reformatted low pass filter having an improved
signal-to-noise ratio.
4. Processing device as claimed in claim 3, further comprising a
comparator installed at the output of the additional filtering
unit, capable of comparing the amplitude of the output signal
supplied by the summation means to a reference value and of
delivering a binary signal at the output of the filtering unit
based on said comparison.
5. Processing device as claimed in claim 4 wherein the comparator
has an adjustable reference value.
6. Processing device as claimed in claim 2, further comprising
inserted between the analog-to-digital converter and the
demodulation means, it includes an estimation unit provided for
estimating the center frequency of the signal after undersampling,
the signal present at the output of the estimation unit being
filtered by a band-pass filter before being applied to the
demodulation means, so as to retain only a single spectral motif
from amongst the plurality of spectral motifs representative of the
signal after undersampling.
7. Processing device as claimed in claim 6 wherein the estimation
unit includes means for determining the parameter N defining the
order of the filters of the plurality Q of finite response filters
of the additional filtering unit, and for configuring the
additional filtering unit with said parameter N.
8. Processing device as claimed in claim 1 wherein the interfering
signal corresponds to the transmission channel noise.
9. Processing device as claimed in claim 1 wherein the sampling
frequency corresponds to at least twice the bandwidth of the signal
transmitted.
10. Processing device as claimed in claim 1 wherein the filter
matched to the spreading code is a digital finite impulse response
filter.
11. A receiver, comprising: an analog-to-digital converter operable
to convert a modulated analog signal into an under-sampled digital
modulated signal, the modulated analog signal including a first
component having a frequency spectrum spread to a first-component
bandwidth according to a spreading code and including a second
component, the converter operable to sample the modulated analog
signal at a sampling frequency at least twice the first-component
bandwidth; a demodulator coupled to the analog-to-digital converter
and operable to recover from the under-sampled signal a demodulated
digital signal including the first and second components having
respective strengths; an emphasizer coupled to the demodulator and
operable to generate a modified demodulated digital signal from the
demodulated digital signal by increasing the strength of the first
component of the demodulated digital signal relative to the
strength of the second component of the demodulated digital signal;
and a de-spreader coupled to the emphasizer and operable to
generate a digital baseband signal from the modified demodulated
digital signal and the spreading code.
12. The receiver of claim 11 wherein the second component of the
modulated analog signal comprises a noise component.
13. The receiver of claim 11, further comprising: an estimator
coupled between the converter and the demodulator and operable to
determine a center frequency of the under-sampled signal; a
band-pass filter coupled between the estimator and the demodulator,
having substantially twice the first-component bandwidth
substantially centered about the center frequency, and operable to
generate a filtered under-sampled signal; and wherein the
demodulator includes, an oscillator operable to generate a
demodulation signal having a frequency substantially equal to the
center frequency; and a mixer coupled to the oscillator, operable
to receive the filtered under-sampled signal from the band-pass
filter, and operable to generate the demodulated digital signal as
a product of the filter under-sampled signal and the demodulation
signal.
14. The receiver of claim 13, further comprising a low-pass filter
coupled between the demodulator and the emphasizer and having
substantially the first-component bandwidth.
15. The receiver of claim 11, further comprising: wherein the
modified demodulated digital signal comprises an amplitude; and a
comparator coupled to the emphasizer and operable to generate a
binary signal having a first level if the amplitude of the modified
demodulated digital signal is greater than a threshold and having a
second level if the amplitude is less than the threshold.
16. The receiver of claim 11 wherein the emphasizer comprises: a
finite-impulse-response filter operable to generate an intermediate
signal from the demodulated digital signal; and a multiplier
coupled to the filter and operable to generate the modified
demodulated digital signal from a product of the intermediate
signal and a predetermined value.
17. The receiver of claim 11 wherein the emphasizer comprises:
finite-impulse-response filters each operable to generate a
respective first intermediate signal from the demodulated digital
signal; multipliers each coupled to a respective filter and each
operable to generate a respective second intermediate signal equal
to a product of a respective first intermediate signal and a
respective predetermined value; and an adder circuit operable to
generate the modified demodulated digital signal from a sum of the
second intermediate signals.
18. The receiver of claim 11 wherein: the first component of the
demodulated digital signal has a symbol rate; and the emphasizer
comprises, a finite-impulse-response filter having an order related
to a quotient of the sampling frequency divided by the symbol rate
and operable to generate an intermediate signal from the
demodulated digital signal, and a multiplier coupled to the filter
and operable to generate the modified demodulated digital signal
from a product of the intermediate signal and a predetermined
value.
19. The receiver of claim 11 wherein the emphasizer comprises: a
finite-impulse-response filter having one or more coefficients
related to an autocorrelation of the spreading code and operable to
generate an intermediate signal from the demodulated digital
signal; and a multiplier coupled to the filter and operable to
generate the modified demodulated digital signal from a product of
the intermediate signal and a predetermined value.
20. The receiver of claim 11 wherein the emphasizer comprises: a
finite-impulse-response filter having one or more coefficients
related to an autocorrelation of the second component of the
modulated analog signal and operable to generate an intermediate
signal from the demodulated digital signal; and a multiplier
coupled to the filter and operable to generate the modified
demodulated digital signal from a product of the intermediate
signal and a predetermined value.
21. The receiver of claim 11 wherein the emphasizer comprises: a
finite-impulse-response filter having coefficients related to
elements of an eigen vector of a product of a variance-covariance
matrix of the spreading code and a transpose of a
variance-covariance matrix of the second component of the modulated
analog signal, the eigen vector being associated with an eigen
value of the product greater than one, the filter operable to
generate an intermediate signal from the demodulated digital
signal; and a multiplier coupled to the filter and operable to
generate the modified demodulated digital signal from a product of
the intermediate signal and a vector value related to a product of
the variance-covariance matrix of the second component of the
demodulated analog signal and the eigen vector.
22. The receiver of claim 11 wherein the emphasizer comprises: a
finite-impulse-response filter having coefficients respectively
equal to elements of an eigen vector of a product of a
variance-covariance matrix of the spreading code and a transpose of
a variance-covariance matrix of the second component of the
modulated analog signal, the eigen vector being associated with an
eigen value of the product greater than one, the filter operable to
generate an intermediate signal from the demodulated digital
signal; and a multiplier coupled to the filter and operable to
generate the modified demodulated digital signal as a vector equal
to a product of the intermediate signal and a vector value equal to
a product of the variance-covariance matrix of the second component
of the demodulated analog signal and the eigen vector.
23. A system, comprising: a receiver, comprising, an
analog-to-digital converter operable to convert a modulated analog
signal into an under-sampled digital modulated signal, the
modulated analog signal including a first component having a
frequency spectrum spread to a first-component bandwidth according
to a spreading code and including a second component, the converter
operable to sample the modulated analog signal at a sampling
frequency at least twice the first-component bandwidth; a
demodulator coupled to the analog-to-digital converter and operable
to recover from the under-sampled signal a demodulated digital
signal including the first and second components having respective
strengths; an emphasizer coupled to the demodulator and operable to
generate a modified demodulated digital signal from the demodulated
digital signal by increasing the strength of the first component of
the demodulated digital signal relative to the strength of the
second component of the demodulated digital signal; and a
de-spreader coupled to the emphasizer and operable to generate a
digital baseband signal from the modified demodulated digital
signal and the spreading code.
24. A method, comprising: receiving a modulated analog signal at a
receiver undersampling the modulated analog signal at a sampling
frequency to generate an under-sampled digital modulated signal,
the modulated analog signal including a first component having a
frequency spectrum spread to a first-component bandwidth according
to a spreading code and including a second component, the sampling
frequency being at least twice the first-component bandwidth;
recovering from the under-sampled signal a demodulated digital
signal including the first and second components having respective
strengths; generating a modified demodulated digital signal from
the demodulated digital signal by reducing the strength of the
second component of the demodulated digital signal relative to the
strength of the first component of the demodulated digital signal;
generating a digital baseband signal from the modified demodulated
digital signal and the spreading code; and outputting the digital
baseband signal at an output of the receiver.
25. The method of claim 24, further comprising: determining a
center frequency of the under-sampled signal; generating a filtered
under-sampled signal having substantially twice the first-component
bandwidth substantially centered about the center frequency; and
wherein recovering includes, generating a demodulation signal
having a frequency substantially equal to the center frequency, and
generating the demodulated digital signal as a product of the
filtered under-sampled signal and the demodulation signal.
26. The method of claim 24, further comprising: limiting a
bandwidth of the demodulated digital signal to substantially the
first-component bandwidth; and generating the modified demodulated
digital signal from the bandwidth-limited demodulated digital
signal.
27. The method of claim 24, further comprising: generating a binary
signal having a first level if an amplitude of the modified
demodulated digital signal is greater than a threshold and having a
second level if the amplitude is less than the threshold; and
wherein generating the digital baseband signal comprises generating
the digital baseband signal from the binary signal.
28. The method of claim 24 wherein generating the modified
demodulated digital signal comprises: generating an intermediate
signal from the demodulated digital signal with a
finite-impulse-response filter; and generating the modified
demodulated digital signal from a product of the intermediate
signal and a predetermined value.
29. The method of claim 24, further comprising: receiving the
modulated analog signal from a propagation channel; and wherein the
second component of the modulated analog signal comprises noise
from the channel.
30. The method of claim 24 wherein generating the modified
demodulated digital signal comprises: generating an intermediate
signal from the demodulated digital signal using a
finite-impulse-response filter; and generating the modified
demodulated digital signal by multiplying the intermediate signal
by a predetermined value.
31. The method of claim 24 wherein generating the modified
demodulated digital signal comprises: generating first intermediate
signals from the demodulated signal using respective
finite-impulse-response filters; generating second intermediate
signals by multiplying each of the first intermediate signals by a
respective predetermined value; and generating the modified
demodulated digital signal by summing together the second
intermediate signals.
32. The method of claim 24 wherein: the first component of the
demodulated digital signal has a symbol rate; and modulating the
demodulated digital signal comprises, generating an intermediate
signal from the demodulated digital signal with a
finite-impulse-response filter having an order related to a
quotient of the sampling frequency divided by the symbol rate, and
generating the modified demodulated digital signal by multiplying
the intermediate signal by a predetermined value.
33. The method of claim 24 wherein generating the modified
demodulated digital signal comprises: generating an intermediate
signal from the demodulated digital signal using a
finite-impulse-response filter having one or more coefficients
related to an autocorrelation of the spreading code; and generating
the modified demodulated digital signal by multiplying the
intermediate signal by a predetermined value.
34. The method of claim 24 wherein generating the modified
demodulated digital signal comprises: generating an intermediate
signal from the demodulated digital signal using a
finite-impulse-response filter having one or more coefficients
related to an autocorrelation of the second component of the
modulated analog signal; and generating the modified demodulated
digital signal by multiplying the intermediate signal by a
predetermined value.
35. The method of claim 24 wherein generating the modified
demodulated digital signal comprises: generating an intermediate
signal from the demodulated digital signal using a
finite-impulse-response filter having one or more coefficients
related to an autocorrelation of the second component of the
demodulated digital signal; and generating the modified demodulated
digital signal by multiplying the intermediate signal by a
predetermined value.
36. The method of claim 24 wherein generating the modified
demodulated digital signal comprises: generating an intermediate
signal from the demodulated digital signal using a
finite-impulse-response filter having coefficients related to
elements of an eigen vector of a product of a variance-covariance
matrix of the spreading code and a transpose of a
variance-covariance matrix of the second component of the modulated
analog signal, the eigen vector being associated with an eigen
value of the product greater than one; and generating the modified
demodulated digital signal by multiplying the intermediate signal
by a vector value related to a product of the variance-covariance
matrix of the second component of the modulated analog signal and
the eigen vector.
37. The method of claim 24 wherein generating the modified
demodulated digital signal comprises: generating an intermediate
signal from the demodulated digital signal using a
finite-impulse-response filter having coefficients related to
elements of an eigen vector of a product of a variance-covariance
matrix of the spreading code and a transpose of a
variance-covariance matrix of the second component of the
demodulated digital signal, the eigen vector being associated with
an eigen value of the product greater than one; and generating the
modified demodulated digital signal by multiplying the intermediate
signal by a vector value related to a product of the
variance-covariance matrix of the second component of the
demodulated digital signal and the eigen vector.
38. The method of claim 24 wherein generating the modified
demodulated digital signal comprises: generating an intermediate
signal from the demodulated digital signal using a
finite-impulse-response filter having coefficients respectively
equal to elements of an eigen vector of a product of a
variance-covariance matrix of the spreading code and a transpose of
a variance-covariance matrix of the second component of the
modulated analog signal, the eigen vector being associated with an
eigen value of the product greater than one; and generating the
modified demodulated digital signal as a vector by multiplying the
intermediate signal by a vector value equal to a product of the
variance-covariance matrix of the second component of the modulated
analog signal and the eigen vector.
Description
PRIORITY CLAIM
This application claims priority from French patent application
Nos. 0504591, filed May 4, 2005, 0504589 filed May 4, 2005, and
0504588, filed May 4, 2005, which are incorporated herein by
reference.
CROSS REFERENCE TO RELATED APPLICATIONS
This application is related to U.S. patent application Ser. No.
11/429,392 entitled RECEIVER DEVICE SUITED TO A TRANSMISSION SYSTEM
USING A DIRECT SEQUENCE SPREAD SPECTRUM and Ser. No. 11/429,674
entitled DIGITAL RECEIVING DEVICE BASED ON AN INPUT COMPARATOR
which have a common filing date and owner and which are
incorporated by reference.
TECHNICAL FIELD
In a general way, an embodiment of the invention relates to the
processing of digital signals and, in particular, the techniques
for decoding such signals. More specifically, an embodiment of the
invention relates to a digital processing device that is arranged
at the input of a radio frequency receiver chain and that is
particularly suited to a transmission system using a direct
sequence spread spectrum, conventionally implemented using phase
modulation of the BPSK type (for "Binary Phase Shift Keying").
BACKGROUND
In a system for transmitting a digital signal using a direct
sequence spread spectrum, the "0" and "1" bits are encoded with
respective symbols sent by the transmitter, and decoded at the
receiver by a finite impulse response (FIR) filter.
In the case where the bits are encoded using a spreading code of
length N, the symbols encoding the "0" and "1" bits are each in the
form of a series of N symbol elements distributed over either of
two different levels and transmitted at a predetermined fixed
frequency F.
The N symbol elements encoding the "1" bit are anti-correlated to
the corresponding N symbol elements encoding the "0" bit, i.e., the
symbol elements of the same rank within both of these two symbols
have opposite values.
For example, if and when a symbol element of the symbol encoding
the "1" bit is at level 1, the corresponding symbol element of the
symbol encoding the "0" bit is at level -1. In the same way, if and
when a symbol element of the symbol encoding the "1" bit is at
level -1, the corresponding symbol element of the symbol encoding
the "0" bit is at level 1.
The development of digital radio frequency (RF) communications,
together with the expansion of mobile telephony, in particular, may
demand the use of multi-standard, very low consumption RF receiver
chains. To reach these objectives, an attempt is made to reduce to
a minimum the difficult-to-program, analog RF circuitry, by
bringing the analog-to-digital converter (ADC) as close as possible
to the receiving antenna. This is then referred to as a
digital/digital/digital receiver chain.
However, a solution such as this may have the effect of increasing
the operating frequency of the ADC in an unreasonable manner. As a
matter of fact, given the frequency of the signals involved in
radio frequency communications, and taking into account the
Shannon-Nyquist Theorem (sampling frequency equal to at least twice
the maximum frequency of the signal being sampled), an operation
such as this may necessitate the use of an ADC whose operating
frequency would be on the order of several gigahertz. Such an ADC
is currently commercially unavailable.
For this reason, it is conventionally impractical to process the
signal digitally from the moment of reception. Nevertheless, this
problem may be solved by undersampling the digital input signal.
This technique, known by the name of undersampling, is based on the
principal of spectrum overlapping and comprises sampling the signal
received, not on the basis of Shannon's Theorem, but at a frequency
greater than twice the signal bandwidth. This is typically valid
only if the signal in question is a narrowband signal, i.e., if the
bandwidth to carrier frequency ratio is significantly lower than
one. Such being the case, the signals involved in the context of RF
communications may be considered as such. As a matter of fact,
their carrier frequency is typically on the order of 2.45 GHz for a
bandwidth of a few MHz. Within this context of narrowband signals,
it becomes possible, according to the undersampling theory, to
sample the signals at a rate much lower than that suggested by the
Shannon Theorem and, more precisely as explained above, at a
sampling frequency that depends only on the bandwidth.
In order to illustrate the foregoing, FIG. 1 is a schematic
representation of a signal receiving and processing chain, wherein
the signal is captured by an antenna 10, then amplified by a
circuit 20 referred to as LNA (for "Low Noise Amplifier") prior to
being submitted to the digital signal processing unit 30, referred
to as DSP (for "Digital Signal Processing"). The output of the DSP
unit may be processed conventionally by a processing unit 40,
referred to as a CPU (for "Central Processing Unit").
FIG. 2 is a schematic representation of the various functional
units involved in the conventional digital solution of the DSP unit
of FIG. 1, which implements undersampling.
The DSP unit includes an analog-to-digital converter 31. The signal
being a narrowband signal, the sampling frequency Fe is not
selected according to the Shannon-Nyquist Theorem, but according to
the undersampling theory. Therefore, Fe is determined
irrespectively of the modulation carrier frequency. In fact, it is
assumed to be equal to at least twice the bandwidth of the binary
message after spread spectrum. For example, for a bandwidth of 2B,
the sampling frequency Fe.gtoreq.4B. Furthermore, the
analog-to-digital converter carries out an M-bit encoding, e.g.,
4-bit.
The ADC is followed by a stage 32 for estimating the new carrier
frequency fp, designating the new center frequency of the signal
after undersampling, and by the phase .phi. corresponding to the
carrier phase. The estimation stage will likewise make it possible
to determine the minimum number of samples necessary for describing
a bit time (Tb), i.e., the time to transmit one bit of the spread
message, which depends, in particular, on the length of the
spreading code used.
According to the undersampling theory, the carrier frequency of the
signal is modified and assumes the following as a new value:
.times. ##EQU00001##
where fm represents the initial carrier frequency and where k
designates a parameter of the undersampling verifying:
<.times. ##EQU00002##
The phase signal after undersampling is estimated by using a phase
estimator.
The signal present at the output of the estimation stage will be
filtered by a band-pass type filter 33, so as to retain only the
base motif of the undersampled signal. As a matter of fact, since
the spectrum of the undersampled signal consists of a multiplicity
of spectral motifs representative of the message, a bandpass
filtering operation is carried out in order to retain only a single
spectral motif. Therefore, the characteristics of this bandpass
filter are as follows:
Center frequency: fp
Bandwidth: 4B
The filter may be either an infinite or finite impulse response
filter (IIR, FIR).
The signal is subsequently brought back to baseband by demodulation
means 34. The undersampled message being conveyed to the carrier
frequency fp, this demodulation step comprises a simple
multiplication step using a frequency fp of phase .phi. sinusoid,
these two characteristic quantities coming from the estimation
stage.
A low pass filtering stage 35 at the output of the demodulation
stage makes it possible to eliminate the harmonic distortion due to
spectral redundancy during demodulation of the signal. As a matter
of fact, the demodulation operation reveals the spectral motif of
the baseband signal but also at twice the demodulation frequency,
i.e., at about the frequency 2fp.
A matched filter stage 36 corresponding to the code of the wanted
signal makes it possible to recover the synchronization of the
signal being decoded with respect to the wanted information. More
precisely, this is a finite impulse response filter, characterized
by its impulse response coefficients {a.sub.i}.sub.i-0, 1, . . . ,
n.
Its structure, described in FIG. 3, is that of a shift register REG
receiving each sample of the input signal IN. The shift register
includes N bistable circuits in the case of symbols with N symbol
elements, which cooperate with a combinational circuit COMB,
designed in a manner known by those skilled in the art and
involving the series of coefficients a.sub.i such that the output
signal OUT produced by the filter has an amplitude directly
dependent upon the level of correlation observed between the
sequence of the N last samples captured by this filter and the
series of the N symbol elements of one of the two symbols, e.g.,
the series of the N elements of the symbol encoding a "1" bit of
the digital signal.
Thus, the matched filtering operation comprises matching the series
of coefficients a.sub.i to the exact replica of the selected
spreading code, in order to correlate the levels of the symbol
elements that it receives in succession at its input to the levels
of the successive symbol elements of one of the two symbols
encoding the "0" and "1" bits, e.g., the symbol elements of the
symbol encoding the "1" bit.
The output signal from the finite impulse response filter 36 can
then be delivered to a comparator capable of comparing the
amplitude of this output signal to a lower threshold value and to
an upper threshold value, in order to generate a piece of binary
information. The comparator is thus equipped to deliver, as a
digital output signal representative of a decoded symbol of the
input signal, a first bit, e.g., "1", when the amplitude of the
output signal of the filter 36 is higher than the value, and a
second bit, e.g., "0", when the amplitude of the output signal of
the additional filter is lower than the lower threshold value.
However, the undersampling technique, which is suitable in this
context, and upon which the digital processing of the signal from
the moment of its reception relies, results in a degradation of the
signal-to-noise ratio after processing, primarily when an
interfering signal (typically the noise of the transmission
channel) cannot be considered a narrowband signal. The conventional
digital receiver chain as just described may have serious
malfunctions once the noise power in the transmission channel
becomes elevated.
As a matter of fact, as a result of the undersampling, the
so-called spectrum overlap phenomenon may conventionally be
observed wherein all of the frequencies higher than half the
sampling frequency are "folded" over the baseband, causing an
unacceptable increase in the noise power in the signal being
processed. This results in an unacceptable error rate at the output
of the decoding process.
This signal-to-noise degradation phenomenon in the transmission
channel, amplified by the undersampling technique employed, is a
principal reason for which the reception solutions based on
digital/digital/digital receiver chains are at present dismissed,
despite the undeniable advantages that they might obtain in terms
of programming and consumption, in particular.
In order to attempt to improve this signal-to-noise ratio degraded
after processing, various solutions may be anticipated, short of
being satisfactory. In particular, it might be anticipated to
increase the power of the signal upon transmission, which, however,
involves a consequential increase in the electrical power consumed
by the circuit. It might also be anticipated to use larger
spectrum-spreading codes, but this would be detrimental to the
speed, which would thereby be greatly reduced.
SUMMARY
In this regard, an embodiment of the invention eliminates these
disadvantages by proposing an improved "digital/digital/digital"
receiver device, capable of correctly decoding a digital signal,
even in the presence of a degradation of the signal-to-noise ratio
after processing. In other words, the embodiment aims to reduce the
error rate at the output of the decoding process for the same
signal-to-noise ratio at the input of a digital/digital/digital
receiver chain.
An embodiment of the invention relates to a digital processing
device for a modulated signal, arranged at the input of a radio
frequency receiver chain, suited in particular to a transmission
system using binary carrier phase modulation by means of a binary
message on which a direct sequence spread spectrum operation has
been carried out, this device comprising an analog-to-digital
converter performing undersampling of the signal received, leading
to an at least partial overlapping of the frequency range of the
undersampled wanted signal by the frequency range of a first
interfering signal corresponding to the noise of the transmission
channel, demodulation means connected at the output of the
analog-to-digital converter in order to bring the undersampled
wanted signal back to baseband, a low pass filter connected at the
output of the demodulation means and a filter matched to the
spreading code used, said device being characterized in that it
includes an additional filtering unit arranged between the low pass
filter and the matched filter, said filtering unit implementing a
stochastic matched filtering operation for improving the
signal-to-noise ratio at the input of the filter matched to the
spreading code.
According to one embodiment, the additional filtering unit includes
a plurality Q of finite impulse response base filters mounted in
parallel, each of which receives an undersampled signal supplied at
the output of the low pass filter, each filter being characterized
by a set of N coefficients, this number N being determined such
that it corresponds to the minimum number of samples for describing
one bit of the spread message, the coefficients of each of the Q
filters corresponding respectively to the components of the Q eigen
vectors associated with at least the Q eigenvalues greater than 1
of the matrix B.sup.-1A, where B is the variance-covariance matrix
of the interfering signal and A the variance-covariance matrix of
the wanted signal.
Advantageously, for each filter of the plurality Q of finite
response filters, the additional filtering unit includes means for
multiplying the signal obtained at the output of said filter, with,
respectively, the central coefficient of the vector resulting from
the product between the variance-covariance matrix of the
interfering signal B and the eigen vector defining the coefficients
of said filter, said unit further comprising means of summing up
the vectors resulting from all of these operations, supplying a
signal corresponding to the output signal of the reformatted low
pass filter having an improved signal-to-noise ratio.
The device according to the above-described embodiment
advantageously includes a comparator installed at the output of the
additional filtering unit, capable of comparing the amplitude of
the output signal supplied by the summation means to a threshold
value and of delivering a binary signal at the output of the
filtering unit based on said comparison.
More preferably, the comparator has an adjustable threshold
value.
According to another characteristic, inserted between the
analog-to-digital converter and the demodulation means, the device
includes an estimation unit provided for estimating the center
frequency of the signal after undersampling, the signal present at
the output of the estimation unit being filtered by a band-pass
filter before being applied to the demodulation means, so as to
retain only a single spectral motif from amongst the plurality of
spectral motifs representative of the signal after
undersampling.
Advantageously, the estimation unit includes means for determining
the parameter N defining the order of the filters of the plurality
Q of finite response filters of the additional filtering unit, and
for configuring the additional filtering unit using said parameter
N.
Also, the sampling frequency corresponds to at least twice the
bandwidth of the signal transmitted.
According to one embodiment, the filter matched to the spreading
code is a digital finite impulse response filter.
BRIEF DESCRIPTION OF THE DRAWINGS
Characteristics and advantages of one or more embodiments of this
invention will become more apparent upon reading the following
description given by way of a non-limiting, illustrative example
and made with reference to the appended figures.
FIG. 1 is a schematic illustration of a conventional receiving and
processing chain for a signal.
FIG. 2 is a schematic illustration of the various functional units
involved in the conventional digital solution of the DSP unit of
FIG. 1.
FIG. 3 is a schematic representation of the structure of a finite
response filter matched to the spreading code used and implemented
in the DSP unit of FIG. 2.
FIG. 4 is a schematic illustration of the design of a DSP unit
according to an embodiment of the invention.
FIG. 5 shows an embodiment of the proposed additional filtering
function at the output of the DSP unit demodulation stage
(including the low pass filter).
DETAILED DESCRIPTION
An embodiment of the invention thus relates to a receiver device
suited to a transmission system using a direct sequence spread
spectrum and of the type comprising a digital processing device
(DSP) for digitizing and processing the signal received at the
moment of reception, by means of undersampling.
This embodiment is designed for receiving and decoding a digital
input signal E composed of bits each of which, based on its "1" or
"0" value, is represented by either of two symbols where each
symbol comprises a series of N symbol elements, distributed over
either of two different levels. These symbols, for example, may
respond to a Barker code.
These symbol elements are delivered at a predetermined fixed
frequency F corresponding to a determined period T=1/F, and the N
symbol elements of the symbol encoding the "1" bit are
anti-correlated to the corresponding N symbol elements of the
symbol encoding the "0" bit.
In order to be able to preserve the advantages in using a
digital/digital/digital receiver device, the structure of which was
described above with reference to FIGS. 1 and 2, while at the same
time increasing its robustness towards noise, it is proposed to add
to the structure of the DSP unit an additional filtering unit
provided for being matched to the signal and mismatched to the
noise.
Therefore, as indicated in FIG. 4, the DSP unit according to an
embodiment of the invention substantially includes, in addition to
the elements already described, an optimal filter 37 such as this,
provided for being positioned between the low pass filter 35 and
the matched filter 36.
The parameter N, used for the configuration of the optimal filter
37, is estimated in the estimation unit 32 and designates the
minimum number of samples for describing one bit-time, namely the
number of samples taken in a period corresponding to the spreading
code. Considering the undersampling frequency (Fe) adopted and the
bit-time defined (Tb) upon transmission, this data is readily
accessible:
##EQU00003##
This data is then used to configure the filtering unit 37.
The addition to the DSP unit according to an embodiment of the
invention of this additional filtering stage 37 arranged after the
demodulation unit (low pass filtering included), and upstream from
the matched filter, has the function of impeding the increase in
noise power caused by spectrum overlap due to the undersampling
operation.
A purpose in using this filter 37 is an improvement in the
signal-to-noise ratio after processing in the digital receiver
chain. In order to accomplish this, as will be explained in detail
below, the unit 37 is based on a filtering technique known per se
by the name of stochastic matched filtering.
A filtering technique such as this makes it possible to define a
bank of Q digital filters FLT1 to FLTQ, mounted in parallel, as
shown in FIG. 5, and provided for being matched to the signal while
at the same time being mismatched to the noise. As concerns the
principle of a stochastic matched filter, if s(t) and b(t) are
considered to be two centered random signals, i.e., zero
mathematical expectation, and if it is assumed that s(t) is the
signal deemed to be of interest, and that b(t) is the interfering
signal with a signal-to-noise ratio defined as being the ratio of
the power of s(t) over the power of b(t), then the stochastic
matched filtering comprises a set of several filters, where each
filter, when applied to the additive mixture s(t)+b(t), improves
the signal-to-noise ratio of the mixture.
The number of filters used depends heavily on the nature of the
noise in the transmission channel, and their order is given by N
(value estimated in the estimation unit 32, as explained
above).
In practice, the N-order filters FLT1 to FLTQ are finite impulse
response (FIR) filters and their structure is similar to that
already described with reference to FIG. 3. Each of these filters,
namely the filters FLT1 to FLTQ, receives, in parallel with the
others, the signal to be decoded, as it is supplied at the output
of the low pass filter 35.
Thus, it is appropriate to properly configure the optimal filtering
unit 37 by selecting, first of all, the respective coefficients of
each of the finite response filters FLT1 to FLTQ, in a way that
makes it possible to improve the signal-to-noise ratio
(transmission channel and quantizing noises) upstream from the
matched filter 36 in the receiver chain. In order to accomplish
this, according to the principles of stochastic matched filtering,
the coefficients of these filters will be determined, on the one
hand, based on the use of statistical parameters representative of
the signal and, on the other hand, the noise.
In practice, the coefficients of each filter actually correspond,
respectively, to the components of certain eigen vectors, recorded
as f.sub.1 to f.sub.q, of the matrix B.sup.-1A, where B is the
variance-covariance matrix of the noise after demodulation and A is
the variance-covariance matrix of the wanted signal. The signals
resulting from the filtering operations with the filters FLT1 to
FLTQ are recorded as S*f1 to S*fQ.
As a matter of fact, the signal received can be represented by a
random vector whose components correspond, in practical terms, to
the samples of the sampled signal.
Let X be such a random vector with countable elements noted as
X.sup.k. The following notations are adopted:
.times..times. ##EQU00004##
From this point of view, the component x.sub.i is a random number
and the component x.sub.i.sup.k is an element of x.sub.i with the
probability pk. The coefficients x.sub.i thus correspond to the
samples of the sampled signal.
The mathematical expectation of x.sub.i, noted as E{x.sub.i}, is
defined as follows:
.times..infin..times..times. ##EQU00005##
This definition thus makes it possible to introduce the
mathematical expectation of such a random vector:
.times..times..times..times. ##EQU00006##
By definition, it is recalled that the variance-covariance matrix
of the random vector X, noted as G, is defined by:
G=E{XX.sup.T}; with XX.sup.T defining the dyad of the vector X by
the vector X, which is also noted as:
.times..times..times..times..times..times..times..times..times..times..ti-
mes..times..times..times..times..times..times..times..times..times..times.-
.times..times..times..times..times..times..times..times..times..times..tim-
es. ##EQU00007##
When the coefficients x.sub.i correspond, as is the case here, to
the samples of a stationary random signal, i.e., E{x.sub.ix.sub.j}
depends only on (j-i), then it is possible to construct the
variance-covariance matrix only from the set of coefficients
E{x.sub.1x.sub.1}, E{x.sub.1x.sub.2}, E{x.sub.1x.sub.3}, . . .
E{x.sub.1x.sub.n}. In this case, these coefficients correspond to
the values assumed by the autocorrelation function of the signal
observed.
In practice, the calculation of the coefficients of the matrices A
and B, respectively, can be performed using the values assumed by
the autocorrelation function of the wanted signal and the noise,
respectively.
As a matter of fact, the fact of spreading the original message
being transmitted will obtain for it certain statistical
properties. In particular, one realizes that its autocorrelation
function corresponds to the deterministic autocorrelation function
of the spreading code used. Advantageously, the autocorrelation
function corresponding to the wanted signal will always be
identical for a given spreading code, irrespective of the message
being transmitted. Thus, when the message being transmitted is
always spread with the same code, the autocorrelation function
associated with the signal remains fixed, the statistics of the
signal actually being more closely linked to the spreading code
used than to the signal itself.
Furthermore, it is also assumed that the noise is stationary, i.e.,
that its statistical characteristics will not vary over time. As a
matter of fact, the noise can be characterized, in terms of
frequencies, by the bandwidth of the low pass filter 34, of which
the cut-off frequency is known. Thus, the autocorrelation function
associated with the noise, which is determined in a known manner
from the spectral density of the noise at the output of the low
pass filter 34, remains invariant. An invariant model is thus
obtained for the autocorrelation function of the noise.
Using the two thus calculated autocorrelation functions for the
wanted signal and for the noise, the variance-covariance matrices A
and B can thus be calculated. The dimensions of the matrices A and
B are equal to N, corresponding to the number of samples required
to describe a bit-time. The eigenvalues and eigen vectors of the
matrix B.sup.-1A can then be calculated.
In fact, the respective coefficients of the N-order filters FLT1 to
FLTQ correspond to the components of the Q eigen vectors associated
with at least the Q eigenvalues greater than 1 of the matrix
B.sup.-1A.
Mathematically speaking, the coefficients of the filters are the
generic coefficients of the eigen vectors f.sub.n defined by the
problem having the following eigenvalues:
Af.sub.n=.lamda..sub.nBf.sub.n, where A represents the
variance-covariance matrix of the wanted signal, and B that of the
noise after demodulation.
Only the eigen vectors f.sub.n associated with the eigenvalues
.lamda..sub.n greater than one are retained. It follows then, that
if Q eigenvalues are greater than 1, the filter bank of the
stochastic matched filtering unit will consist of Q filters.
As a matter of fact, all of the eigen vectors of the matrix
B.sup.-1A associated with eigenvalues greater than 1 are
representative of the signal, and all of the eigen vectors of the
matrix B.sup.-1A associated with eigenvalues lesser than 1 are
representative of the noise. In other words, only the eigen vectors
of the matrix B.sup.-1A associated with eigenvalues greater than 1
improve the signal-to-noise ratio.
Therefore, the signal S at the output of the low pass filter is
filtered by the Q filters FLT1 to FLTQ arranged in parallel, the
coefficients of which correspond to the components of the
N-dimension eigen vectors f.sub.1 to f.sub.q associated,
respectively, with the Q eigenvalues greater than 1 of the matrix
B.sup.-1A. The coefficients S*f.sub.n, with n falling between 1 and
Q, thus represent the signal S filtered by the filters FLT1 to
FLTQ.
At this stage, the overall signal-to-noise ratio is improved, but
the processing carried out has greatly deformed the original
signal. It may then be necessary to reconstruct the signal from the
signals S*f.sub.n with n falling between 1 and Q.
In order to accomplish this, at the output of each filter FLT1 to
FLTQ, multiplication means M.sub.1 to M.sub.Q enable the signal
obtained to be multiplied by the central coefficient y.sub.n of the
vector y.sub.n, obtained from the product between the
variance-covariance matrix B of the noises and the previously
defined associated vector f.sub.n:
Y.sub.n=Bf.sub.n, this relationship being understood as the product
of the matrix B and the vector f.sub.n, with n falling between 1
and Q.
It is to be noted that there will therefore be as many vectors
Y.sub.n as filters FLTQ.
Each of the coefficients S*f.sub.n is therefore multiplied by the
central coefficient y.sub.n, with n falling between 1 and Q.
Summation means P.sub.1 to P.sub.Q-1 are then provided in order to
sum up the vectors resulting from all of these operations, so as to
obtain, at the output, a vector S of length N, having the
formula:
.times..times. ##EQU00008##
The signal {tilde over (S)} is thus a reformatted signal having a
more favorable signal-to-noise ratio than the signal S at the input
of the device, the filters FLT1 to FLTQ being optimal in one
embodiment in terms of the signal-to-noise ratio.
This signal is then supplied to the input of a comparator COMP in
order to be compared to a threshold value V0, thereby making it
possible to recover a binary signal {tilde over (S)}b at the output
of the stochastic matched filtering unit. The processing then
continues in a conventional manner using the matched filter 36.
Advantageously, as a result of the matched filtering unit, a signal
having a much better quality, in terms of the signal-to-noise
ratio, exists at the input of the matched filter 36, which will
make it much easier to select the synchronization of the wanted
signal in the matched filter 36.
A configuration example of an optimal filter 37 according to an
embodiment of the invention, which is involved in the receiver
chain via undersampling, is presented hereinbelow. In this example
the signal to be encoded and transmitted has a bandwidth B=2 MHz.
Said signal will be encoded by a Barker code of length 11 and
modulated by a carrier frequency of 2.45 GHz.
The encoded signal is modulated and transmitted in the transmission
channel, then received by an RF antenna and amplified by an LNA. It
is recognized that the signal has experienced the interference from
the transmission channel, which is assumed to have very low
correlation (white noise). To be able to observe the effectiveness
of adding the stochastic matched filtering unit, the situation will
be used in which the signal-to-noise ratio (SNR) is equal to 0 dB.
In this specific case, the conventional digital chain supplies
unsatisfactory results.
The undersampling frequency Fe in the ADC is fixed as
Fe.gtoreq.4B=8 MHz. In this case, Fe=4B=8 MHz.
As was seen, the parameters that define the characteristics of the
filters are Q and N, i.e., their number and order, respectively. In
our example, N is equal to 5; each filter will thus be of the fifth
order. The calculations performed according to the principles set
forth above result in the assumption that Q is equal to 3, which
provides the number of filters of the fifth order that are used.
The filters Y.sub.n serve only to supply the mean coefficient
y.sub.n. The Table below (Tab. 1) supplies the various coefficients
of the optimal filter for the f.sub.n, Y.sub.n and y.sub.n
considered in our example, with n falling between 1 and 3.
TABLE-US-00001 TABLE 1 Coefficients of the optimal filter 37 with N
= 5 and Q = 3. N = 1 N = 2 N = 3 N = 4 N = 5 f1(Q = 1) 0.5899
-0.9174 1.2715 -0.9147 0.5899 f2(Q = 2) -0.7892 0.5078 -0.0000
-0.5078 0.7892 f3(Q = 3) 0.4360 0.5652 0.5072 0.5652 0.4360 Y1(Q =
1) 0.1404 -0.2444 y1 = 0.3034 -0.2444 0.1404 Y2(Q = 2 -0.5283
0.1636 y2 = 0.000 -0.1636 0.5283 Y3(Q = 3) 0.1859 0.4969 y3 =
0.5445 0.4969 0.1859
With a configuration of the optimal filter according to the values
in Table 1, a significant improvement in the signal-to-noise ratio
can be observed. As a matter of fact, between the output of the low
pass filter 35 and the output of the optimal filter 37, the SNR
passes from 1.2 db to 5.25 db.
Generally speaking, the addition of the optimal filter 37 to the
receiver chain makes it possible to increase the signal-to-noise
ratio, prior to using the matched filter 36, an average of 4 to 5
dB. To illustrate this effect, the two tables below (Tab. 2 and
Tab. 3) supply the signal-to-noise ratio (SNR) at various points
along the chain, for a conventional chain (FIG. 2) and for a chain
with an optimal filter based on stochastic matched filtering (FIG.
3), respectively, and the number of resulting bit errors per 1,000
bit-times of the chain. It appears that the number of bit errors is
sharply reduced with the addition of an optimal filter, as compared
to the conventional solution.
TABLE-US-00002 TABLE 2 Simulation per 1,000 bit-times for the
conventional receiver chain. Pre-matched Number of bit Receiver SNR
Post-ADC SNR filter SNR errors/1,000 5 dB 6.8 dB 7 dB 0 3 dB 5.4 dB
6.5 dB 4 0 dB 1.2 dB 1.37 dB 205
TABLE-US-00003 TABLE 3 Simulation per 1,000 bit-times for the
receiver chain with optimal filter 37 according to an embodiment of
the invention. Pre-matched Number of bit Receiver SNR Post-ADC SNR
filter SNR errors/1,000 5 dB 6.8 dB 11 dB 0 3 dB 5.4 dB 10.6 dB 0 0
dB 1.2 dB 5.25 dB 20
Thus, the use of an optimal filter according to an embodiment of
the invention in the processing chain may make it possible to
utilize a digital/digital/digital chain in RF communications, even
in a noisy environment. By comparison to a conventional approach,
this structure makes it possible to bring about a reduction of the
costs (in terms of power consumed), but also an increase in the
speed and range of transmission.
An electronic system, such as a cell phone or wireless LAN, may
incorporate the RF part of FIG. 4 according to an embodiment of the
invention.
From the foregoing it will be appreciated that, although specific
embodiments of the invention have been described herein for
purposes of illustration, various modifications may be made without
deviating from the spirit and scope of the invention.
* * * * *
References